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Offers a well-rounded, mathematical approach to problems in signal interpretation using the latest time, frequency, and mixed-domain methods _ Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques _ Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis _ Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more
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Offers a well-rounded, mathematical approach to problems in signal interpretation using the latest time, frequency, and mixed-domain methods
_ Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques
_ Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis
_ Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
_ Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques
_ Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis
_ Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 960
- Erscheinungstermin: 2. Januar 2004
- Englisch
- Abmessung: 240mm x 161mm x 55mm
- Gewicht: 1460g
- ISBN-13: 9780471234418
- ISBN-10: 0471234419
- Artikelnr.: 11412253
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 960
- Erscheinungstermin: 2. Januar 2004
- Englisch
- Abmessung: 240mm x 161mm x 55mm
- Gewicht: 1460g
- ISBN-13: 9780471234418
- ISBN-10: 0471234419
- Artikelnr.: 11412253
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Preface. Acknowledgments. 1 Signals: Analog, Discrete, and Digital. 1.1
Introduction to Signals. 1.2 Analog Signals. 1.3 Discrete Signals. 1.4
Sampling and Interpolation. 1.5 Periodic Signals. 1.6 Special Signal
Classes. 1.7 Signals and Complex Numbers. 1.8 Random Signals and Noise. 1.9
Summary. References. Problems. 2 Discrete Systems and Signal Spaces. 2.1
Operations on Signals. 2.2 Linear Systems. 2.3 Translation Invariant
Systems. 2.4 Convolutional Systems. 2.5 The l¯p Signal Spaces. 2.6 Inner
Product Spaces. 2.7 Hilbert Spaces. 2.8 Summary. References. Problems. 3
Analog Systems and Signal Spaces. 3.1 Analog Systems. 3.2 Convolution and
Analog LTI Systems. 3.3 Analog Signal Spaces. 3.4 Modern Integration
Theory. 3.5 Distributions. 3.6 Summary. References. Problems. 4 Time-Domain
Signal Analysis. 4.1 Segmentation. 4.2 Thresholding. 4.3 Texture. 4.4
Filtering and Enhancement. 4.5 Edge Detection. 4.6 Pattern Detection. 4.7
Scale Space. 4.8 Summary. References. Problems. 5 Fourier Transforms of
Analog Signals. 5.1 Fourier Series. 5.2 Fourier Transform. 5.3 Extension to
L2(R). 5.4 Summary. References. Problems. 6 Generalized Fourier Transforms
of Analog Signals. 6.1 Distribution Theory and Fourier Transforms. 6.2
Generalized Functions and Fourier Series Coefficients. 6.3 Linear Systems
in the Frequency Domain. 6.4 Introduction to Filters. 6.5 Modulation. 6.6
Summary. References. Problems. 7 Discrete Fourier Transforms. 7.1 Discrete
Fourier Transform. 7.2 Discrete-Time Fourier Transform. 7.3 The Sampling
Theorem. 7.4 Summary. References. Problems. 8 The z-Transform. 8.1
Conceptual Foundations. 8.2 Inversion Methods. 8.3 Related Transforms. 8.4
Summary. References. Problems. 9 Frequency-Domain Signal Analysis. 9.1
Narrowband Signal Analysis. 9.2 Frequency and Phase Estimation. 9.3
Discrete filter design and implementation. 9.4 Wideband Signal Analysis.
9.5 Analog Filters. 9.6 Specialized Frequency-Domain Techniques. 9.7
Summary. References. Problems. 10 Time-Frequency Signal Transforms. 10.1
Gabor Transforms. 10.2 Short-Time Fourier Transforms. 10.3 Discretization.
10.4 Quadratic Time-Frequency Transforms. 10.5 The Balian-Low Theorem. 10.6
Summary. References. Problems. 11 Time-Scale Signal Transforms. 11.1 Signal
Scale. 11.2 Continuous Wavelet Transforms. 11.3 Frames. 11.4
Multiresolution Analysis and Orthogonal Wavelets. 11.5 Summary. References.
Problems. 12 Mixed-Domain Signal Analysis. 12.1 Wavelet Methods for Signal
Structure. 12.2 Mixed-Domain Signal Processing. 12.3 Biophysical
Applications. 12.4 Discovering Signal Structure. 12.5 Pattern Recognition
Networks. 12.6 Signal Modeling and Matching. 12.7 Afterword. References.
Problems. Index.
Introduction to Signals. 1.2 Analog Signals. 1.3 Discrete Signals. 1.4
Sampling and Interpolation. 1.5 Periodic Signals. 1.6 Special Signal
Classes. 1.7 Signals and Complex Numbers. 1.8 Random Signals and Noise. 1.9
Summary. References. Problems. 2 Discrete Systems and Signal Spaces. 2.1
Operations on Signals. 2.2 Linear Systems. 2.3 Translation Invariant
Systems. 2.4 Convolutional Systems. 2.5 The l¯p Signal Spaces. 2.6 Inner
Product Spaces. 2.7 Hilbert Spaces. 2.8 Summary. References. Problems. 3
Analog Systems and Signal Spaces. 3.1 Analog Systems. 3.2 Convolution and
Analog LTI Systems. 3.3 Analog Signal Spaces. 3.4 Modern Integration
Theory. 3.5 Distributions. 3.6 Summary. References. Problems. 4 Time-Domain
Signal Analysis. 4.1 Segmentation. 4.2 Thresholding. 4.3 Texture. 4.4
Filtering and Enhancement. 4.5 Edge Detection. 4.6 Pattern Detection. 4.7
Scale Space. 4.8 Summary. References. Problems. 5 Fourier Transforms of
Analog Signals. 5.1 Fourier Series. 5.2 Fourier Transform. 5.3 Extension to
L2(R). 5.4 Summary. References. Problems. 6 Generalized Fourier Transforms
of Analog Signals. 6.1 Distribution Theory and Fourier Transforms. 6.2
Generalized Functions and Fourier Series Coefficients. 6.3 Linear Systems
in the Frequency Domain. 6.4 Introduction to Filters. 6.5 Modulation. 6.6
Summary. References. Problems. 7 Discrete Fourier Transforms. 7.1 Discrete
Fourier Transform. 7.2 Discrete-Time Fourier Transform. 7.3 The Sampling
Theorem. 7.4 Summary. References. Problems. 8 The z-Transform. 8.1
Conceptual Foundations. 8.2 Inversion Methods. 8.3 Related Transforms. 8.4
Summary. References. Problems. 9 Frequency-Domain Signal Analysis. 9.1
Narrowband Signal Analysis. 9.2 Frequency and Phase Estimation. 9.3
Discrete filter design and implementation. 9.4 Wideband Signal Analysis.
9.5 Analog Filters. 9.6 Specialized Frequency-Domain Techniques. 9.7
Summary. References. Problems. 10 Time-Frequency Signal Transforms. 10.1
Gabor Transforms. 10.2 Short-Time Fourier Transforms. 10.3 Discretization.
10.4 Quadratic Time-Frequency Transforms. 10.5 The Balian-Low Theorem. 10.6
Summary. References. Problems. 11 Time-Scale Signal Transforms. 11.1 Signal
Scale. 11.2 Continuous Wavelet Transforms. 11.3 Frames. 11.4
Multiresolution Analysis and Orthogonal Wavelets. 11.5 Summary. References.
Problems. 12 Mixed-Domain Signal Analysis. 12.1 Wavelet Methods for Signal
Structure. 12.2 Mixed-Domain Signal Processing. 12.3 Biophysical
Applications. 12.4 Discovering Signal Structure. 12.5 Pattern Recognition
Networks. 12.6 Signal Modeling and Matching. 12.7 Afterword. References.
Problems. Index.
Preface. Acknowledgments. 1 Signals: Analog, Discrete, and Digital. 1.1
Introduction to Signals. 1.2 Analog Signals. 1.3 Discrete Signals. 1.4
Sampling and Interpolation. 1.5 Periodic Signals. 1.6 Special Signal
Classes. 1.7 Signals and Complex Numbers. 1.8 Random Signals and Noise. 1.9
Summary. References. Problems. 2 Discrete Systems and Signal Spaces. 2.1
Operations on Signals. 2.2 Linear Systems. 2.3 Translation Invariant
Systems. 2.4 Convolutional Systems. 2.5 The l¯p Signal Spaces. 2.6 Inner
Product Spaces. 2.7 Hilbert Spaces. 2.8 Summary. References. Problems. 3
Analog Systems and Signal Spaces. 3.1 Analog Systems. 3.2 Convolution and
Analog LTI Systems. 3.3 Analog Signal Spaces. 3.4 Modern Integration
Theory. 3.5 Distributions. 3.6 Summary. References. Problems. 4 Time-Domain
Signal Analysis. 4.1 Segmentation. 4.2 Thresholding. 4.3 Texture. 4.4
Filtering and Enhancement. 4.5 Edge Detection. 4.6 Pattern Detection. 4.7
Scale Space. 4.8 Summary. References. Problems. 5 Fourier Transforms of
Analog Signals. 5.1 Fourier Series. 5.2 Fourier Transform. 5.3 Extension to
L2(R). 5.4 Summary. References. Problems. 6 Generalized Fourier Transforms
of Analog Signals. 6.1 Distribution Theory and Fourier Transforms. 6.2
Generalized Functions and Fourier Series Coefficients. 6.3 Linear Systems
in the Frequency Domain. 6.4 Introduction to Filters. 6.5 Modulation. 6.6
Summary. References. Problems. 7 Discrete Fourier Transforms. 7.1 Discrete
Fourier Transform. 7.2 Discrete-Time Fourier Transform. 7.3 The Sampling
Theorem. 7.4 Summary. References. Problems. 8 The z-Transform. 8.1
Conceptual Foundations. 8.2 Inversion Methods. 8.3 Related Transforms. 8.4
Summary. References. Problems. 9 Frequency-Domain Signal Analysis. 9.1
Narrowband Signal Analysis. 9.2 Frequency and Phase Estimation. 9.3
Discrete filter design and implementation. 9.4 Wideband Signal Analysis.
9.5 Analog Filters. 9.6 Specialized Frequency-Domain Techniques. 9.7
Summary. References. Problems. 10 Time-Frequency Signal Transforms. 10.1
Gabor Transforms. 10.2 Short-Time Fourier Transforms. 10.3 Discretization.
10.4 Quadratic Time-Frequency Transforms. 10.5 The Balian-Low Theorem. 10.6
Summary. References. Problems. 11 Time-Scale Signal Transforms. 11.1 Signal
Scale. 11.2 Continuous Wavelet Transforms. 11.3 Frames. 11.4
Multiresolution Analysis and Orthogonal Wavelets. 11.5 Summary. References.
Problems. 12 Mixed-Domain Signal Analysis. 12.1 Wavelet Methods for Signal
Structure. 12.2 Mixed-Domain Signal Processing. 12.3 Biophysical
Applications. 12.4 Discovering Signal Structure. 12.5 Pattern Recognition
Networks. 12.6 Signal Modeling and Matching. 12.7 Afterword. References.
Problems. Index.
Introduction to Signals. 1.2 Analog Signals. 1.3 Discrete Signals. 1.4
Sampling and Interpolation. 1.5 Periodic Signals. 1.6 Special Signal
Classes. 1.7 Signals and Complex Numbers. 1.8 Random Signals and Noise. 1.9
Summary. References. Problems. 2 Discrete Systems and Signal Spaces. 2.1
Operations on Signals. 2.2 Linear Systems. 2.3 Translation Invariant
Systems. 2.4 Convolutional Systems. 2.5 The l¯p Signal Spaces. 2.6 Inner
Product Spaces. 2.7 Hilbert Spaces. 2.8 Summary. References. Problems. 3
Analog Systems and Signal Spaces. 3.1 Analog Systems. 3.2 Convolution and
Analog LTI Systems. 3.3 Analog Signal Spaces. 3.4 Modern Integration
Theory. 3.5 Distributions. 3.6 Summary. References. Problems. 4 Time-Domain
Signal Analysis. 4.1 Segmentation. 4.2 Thresholding. 4.3 Texture. 4.4
Filtering and Enhancement. 4.5 Edge Detection. 4.6 Pattern Detection. 4.7
Scale Space. 4.8 Summary. References. Problems. 5 Fourier Transforms of
Analog Signals. 5.1 Fourier Series. 5.2 Fourier Transform. 5.3 Extension to
L2(R). 5.4 Summary. References. Problems. 6 Generalized Fourier Transforms
of Analog Signals. 6.1 Distribution Theory and Fourier Transforms. 6.2
Generalized Functions and Fourier Series Coefficients. 6.3 Linear Systems
in the Frequency Domain. 6.4 Introduction to Filters. 6.5 Modulation. 6.6
Summary. References. Problems. 7 Discrete Fourier Transforms. 7.1 Discrete
Fourier Transform. 7.2 Discrete-Time Fourier Transform. 7.3 The Sampling
Theorem. 7.4 Summary. References. Problems. 8 The z-Transform. 8.1
Conceptual Foundations. 8.2 Inversion Methods. 8.3 Related Transforms. 8.4
Summary. References. Problems. 9 Frequency-Domain Signal Analysis. 9.1
Narrowband Signal Analysis. 9.2 Frequency and Phase Estimation. 9.3
Discrete filter design and implementation. 9.4 Wideband Signal Analysis.
9.5 Analog Filters. 9.6 Specialized Frequency-Domain Techniques. 9.7
Summary. References. Problems. 10 Time-Frequency Signal Transforms. 10.1
Gabor Transforms. 10.2 Short-Time Fourier Transforms. 10.3 Discretization.
10.4 Quadratic Time-Frequency Transforms. 10.5 The Balian-Low Theorem. 10.6
Summary. References. Problems. 11 Time-Scale Signal Transforms. 11.1 Signal
Scale. 11.2 Continuous Wavelet Transforms. 11.3 Frames. 11.4
Multiresolution Analysis and Orthogonal Wavelets. 11.5 Summary. References.
Problems. 12 Mixed-Domain Signal Analysis. 12.1 Wavelet Methods for Signal
Structure. 12.2 Mixed-Domain Signal Processing. 12.3 Biophysical
Applications. 12.4 Discovering Signal Structure. 12.5 Pattern Recognition
Networks. 12.6 Signal Modeling and Matching. 12.7 Afterword. References.
Problems. Index.